Abstract in Englisch:

Partial least squares (PLS) is an efficient approach for multivariate statistical process monitoring. Although it works in many industrial applications, Zhou et al. [2010] revealed that some properties of PLS algorithm may hamper overall efficiency of process monitoring scheme. To solve these problems, a modified approach is proposed in this paper. Compared with the existing PLS approaches, the new approach performs an orthogonal decomposition on regression variable space to eliminate the variations useless for output prediction. Based on the new approach, a complete process monitoring scheme is also developed. Finally, the effectiveness of the proposed approach is verified on an industrial benchmark of Tennessee Eastman process.